python visualizes too much data using the plotly database

Too much data 1 second. Good day 9w data. The data is graphed out as a line graph, which is a bar graph. How can we reduce the interval such as database query every 10 to get one. Or plotly when drawing a graph, do it every 10 times

import os
import numpy as np
import pandas as pd
import sqlite3
import plotly as py
import plotly.graph_objs as go
#import plotly.expression as px
from plotly import tools
import datetime

import warnings
warnings.filterwarnings("ignore")
# 使用8266 dht11做到温湿度采集。上传到腾讯我的vos服务器，自己做的http接受字符串程序
# 使用8266 dht11做到温湿度采集。上传到腾讯我的vos服务器，自己做的http接受字符串程序
#建立数据库连接
#conn = pymysql.connect("192.168.6.128","root","root","test_db",charset="utf8")
con=sqlite3.connect("220604_temp_dht11.db")
print("连接成功")
#读取数据库表数据
cursor = con.cursor()
#dataCopy = cursor.execute("select * from t1 where sdate>'2022-05-04' order by id desc   ")
#dataCopy = cursor.execute("select * from t1  order by id desc Limit 15000  ")
dataCopy = cursor.execute("select * from t1  order by id desc  ")
#data = pd.read_sql("select * from t1 Limit 100 order by id desc ",con=con)
values = dataCopy.fetchall()
#for row in values:
# 使用Pandas的DataFrame来处理每一行要比使用一个包含元组的元组方便
 # 下面的Python代码片段将所有行转化为DataFrame实例
df = pd.DataFrame([[ij for ij in i] for i in values])
# print(df) 
# 步骤一
df.rename(columns={0: 'id', 1: 'tt', 2: 'hh', 4: 'sdate'}, inplace=True)
#xx=datetime.datetime.strftime(df["sdate"],'%Y-%m-%d')
trace0 = go.Scatter(x=df["sdate"],y=df["tt"],name="温度")
trace1 = go.Scatter(x=df["sdate"],y=df["hh"],name="湿度")
# 步骤二
data = [trace0,trace1]
# 步骤三
fig = go.Figure(data)
# 步骤四
fig.update_layout(


    xaxis_title="年份",
    yaxis_title="温湿度"
)
# 步骤五
output_path = "C:/bar.html"
py.offline.plot(fig, filename=output_path)
#fig.show()